Background Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. Results Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. Conclusions This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.
Elevating AGEs in rabbits can accelerate the articular cartilage degradation that occurs with physical exercise, and pioglitazone can reduce the severity of the AGEs-induced OA in a rabbit model.
Apoptosis is a widespread phenomenon and its dysregulation may result in a variety of human pathologies, such as cancer, autoimmune diseases and neurodegenerative disorders. CXXC-type zinc finger protein 5 (CXXC5) is commonly considered as a tumor suppressor undergoing deregulation or deletion in hematonosis. But it has implied involvement in apoptosis indirectly and the molecular mechanism remains unknown. In this study, we investigated CXXC5-induced apoptosis as well as its underlying mechanism. A fluorescence resonance energy transfer (FRET) assay suggested that CXXC5 induced cell death and caspase-3 activity in primary rat cortical neurons. Further colorimetric TUNEL assay, Hoechst staining and flow cytometric assay indicated a time-dependent apoptosis in which the activities of caspase-8 and caspase-3 were both regulated via CXXC5 according to enzymatic activity assay, Hoechst staining and Western blotting. Transcription reporter assay and Western blotting showed that CXXC5 resulted in activation of tumor necrosis factor-α (TNF-α), initiated the extrinsic apoptosis pathway and cross-linked with the intrinsic mitochondrial pathway. Being a bone morphogenetic protein 4 (BMP-4) downstream regulator, and also a transcription factor, cellular co-localization and co-immunoprecipitation results indicate that CXXC5 co-localized and interacted with Smads. Western blotting and nuclear fraction extraction implied that CXXC5 facilitated Smad3 phosphorylation and Smad4 nuclear translocation, and that co-expression of Smad together with CXXC5 resulted in higher TNF-α reporter activity. In sum, CXXC5 appears to regulate the TNF-α apoptosis pathway by associating with Smads.
It is shown that by experimentally controlling a weak optical lattice potential to equilibrate the interatomic interactions, we can construct a set of exact solutions of the Gross-Pitaevskii equations (GPE) for a two-component Bose-Einstein condensate (BEC). The exact solutions describe some balance superfluid phases with different flow-density amplitudes that supply several different and useful sources of the atom lasers. In the definition of dynamical superfluid-insulator transition (DSIT), (see Smerzi A. et al., Phys. Rev. Lett., 89 (2002) 170402), the DSITs from the balance superfluid phases to the balance insulator phases are studied. The DSITs can be detected experimentally by observing the deformation of the periodic structure and the losses of the interference pattern and stability.
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